Much work has been done in SLAM using 5G signals, also called 5G SLAM, including geometry-based methods [1]}, [2]}, which cannot provide uncertainty information; message passing methods [3]}, [4]}, [5]}, which provide uncertainty information, but are inherently sub-optimal; more powerful algorithms using rfs theory [6]}, [7]}, [8]}, [9]}, [10]}. The latter class of algorithms can handle the data association (DA) problem between measurements and landmarks [11]} and have certain optimality guarantees. In particular, probability hypothesis density (PHD) filters are used in [6]}, [7]}, PMBM filters are used in [8]}, [9]}, [10]}, and the low-computational version PMB filters are also applied in [10]}. Because PMB(M) filters enumerate all possible DAs explicitly, they provide more accurate results than PHD filters in 5G SLAM, as shown in [10]}.
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